Bioinformatics approaches have been widely utilized in genome mining for bacterial mobile genetic elements. Over the years we have developed several bioinformatics tools/databases focused on genomic island identification, mobility analysis and stability maintenance, includes:
(i) the web-based tools for genomce comparative analysis: mpiBLAST-based mGenomeSubtractor for in silico subtractive hybridization of bacterial genomes and MobilomeFINDER for in silico and experimental discovery of bacterial genomic islands;
(ii) the open-access databases: the ICEberg database of integrative and conjugative elements, SecReT4 of type IV secretion system, TADB of type 2 toxin-antitoxin loci, dndDB of phosphorothioation of the DNA backbone;
(iii) the online tool ThioFinder for thiopeptide biosynthetic gene cluster detection.

dndDB, 2009
A database focused on phosphorothioation of the DNA backbone.

ThioBase , 2012
A embedded database of ThioFinder. It contains the 99 known thiopeptide information regarding the chemical structure, biological activity, producing organism, and biosynthetic gene (cluster) along with the associated genome if available.

The group leader, Dr. Hong-Yu OU, had been involved into the development of the following tool/database before he worked independently at Shanghai Jiao Tong University in June 2006.

(1) tRNAcc, 2006
A novel strategy developed at University of Leicester, UK for identification of genomic islands by comparative analysis of the contents and contexts of tRNA sites in closely related bacteria. The web-based tool is now available at the MobilomeFINDER server.

(2) ArrayOme, 2005
A new program developed at University of Leicester, UK to calculate the size of genomes represented by microarray-based probes and facilitate recognition of key bacterial strains carrying large numbers of novel genes. It is now available at the MobilomeFINDER server.

(3) GS-Finder, 2004
A self-training algorithm GS-Finder, developed at Tianjin University, is proposed to recognize translation start sites in bacterial genomes without a prior knowledge of rRNA in the genomes concerned. It can be used to relocate the translation start sites of putative CDSs of genomes, which are predicted by gene finding programs (e.g. Glimmer 2.02).

(4) Zcurve 1.0, 2003
A program Zcurve 1.0, developed at Tianjin University, for recognizing protein-coding genes in bacterial and archaeal genomes.

(5) ZCURVE_CoV 1.0, 2003
A online tool ZCURVE_CoV 1.0, developed at Tianjin University, to recognize protein coding genes in coronavirus genomes, specially suitable for SARS-CoV genomes has been proposed. Compared with some existing systems, the new program package has the merits of simplicity, high accuracy, reliability and quickness. ZCURVE_CoV 2.0 is an improved version, in which the prediction of cleavage sites of viral proteinases in polyproteins has been taken into account.

(6) DEG 1.0, 2004
The database DEG 1.0, developed at Tianjin University, contains available essential genes among a wide range of organisms.

(7) Z curve database, 2003
The Z curve database, developed at Tianjin University, a graphic representation of genome sequences by using the Zcurve method.

(8) ORFs flower, 2003
an interesting clustering phenomenon of ORFs in the bacterial genomes with high G+C content.